Bibliographic record
Abstract
Abstract An analysis method proposed by Huang is improved and used to dissect the radiative forcing in the instantaneous quadrupling CO2 experiment from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Multiple validation tests show that the errors in the forcing estimates are generally within 10%. The results show that quadrupling CO2, on average, induces a global-mean all-sky instantaneous top-of-the-atmosphere forcing of 5.4 W m−2, which is amended by a stratospheric adjustment of 1.9 W m−2 and a tropospheric adjustment of −0.1 W m−2. The resulting fully adjusted radiative forcing has an ensemble mean of 7.2 W m−2 and a substantial intermodel spread (maximum–minimum) of 2.4 W m−2, which results from all the forcing components, especially the instantaneous forcing and tropospheric adjustment. The fidelity of the linear decomposition of the overall radiation variation is improved when forcing is explicitly estimated for each model. A significant contribution by forcing uncertainty to the intermodel spread of the surface temperature projection is verified. The results reaffirm the importance of evaluating the radiative forcing components in climate feedback analyses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".